Statistics, effective number of correlations

For a correlation free experiment, \( \tau \) equals 1. From the point of view of eq. (18) we can interpret a sequential correlation as an effective reduction of the number of measurements by a factor \( \tau \). The effective number of measurements becomes:

$$ n_\mathrm{eff} = \frac{n}{\tau} $$

To neglect the autocorrelation time \( \tau \) will always cause our simple uncorrelated estimate of \( \mathrm{err}_X^2\approx \mathrm{var}(x)/n \) to be less than the true sample error. The estimate of the error will be too good. On the other hand, the calculation of the full autocorrelation time poses an efficiency problem if the set of measurements is very large.